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Aerodynamic inverse optimization with genetic algorithms

机译:遗传算法的气动逆优化

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摘要

A multiobjective genetic algorithm based on Fonseca-Fleming's Pareto ranking method has been applied to optimize the three-dimensional target pressures for the aerodynamic inverse design of wing shape. The optimization problem was formulated to minimize the induced drag for wings as well as to minimize the viscous drag for airfoil sections. Performances of both the simple genetic algorithm and vector evaluated genetic algorithm were found unsatisfactory to the present optimization problem. The present design procedure was successfully applied to transonic wing design.
机译:应用基于Fonseca-Fleming的Pareto排序方法的多目标遗传算法,优化了机翼形状的空气动力学逆向设计的三维目标压力。制定了优化问题,以最大程度地减小机翼引起的阻力,并减小机翼截面的粘性阻力。发现简单遗传算法和矢量评估遗传算法的性能都不能满足当前的优化问题。本设计程序已成功应用于跨音速机翼设计。

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